Computer vision-based method for detecting cracks in reservoir dams

Bo Qi; Wenang Hou

doi:10.1117/12.3012471

21 December 2023 Computer vision-based method for detecting cracks in reservoir dams

Bo Qi, Wenang Hou

Proceedings Volume 12970, Fourth International Conference on Signal Processing and Computer Science (SPCS 2023); 129702T (2023) https://doi.org/10.1117/12.3012471
Event: Fourth International Conference on Signal Processing and Computer Science (SPCS 2023), 2023, Guilin, China

Abstract

Reservoir dams serve as critical infrastructure. However, during their prolonged operation, cracks tend to appear on surfaces, particularly on slopes. The development of cracks poses risks to the stability of reservoir dams. This paper employs computer vision and deep learning methods to analyze images of reservoir dams. The primary directional characteristics of dam cracks are identified by leveraging deep learning method, and the distinctive features of cracks are calculated by utilizing the OpenCV platform and filtering techniques. Additionally, the fundamental features of cracks are determined through analysis and calculations using crack images of a dam as an example.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Bo Qi and Wenang Hou "Computer vision-based method for detecting cracks in reservoir dams", Proc. SPIE 12970, Fourth International Conference on Signal Processing and Computer Science (SPCS 2023), 129702T (21 December 2023); https://doi.org/10.1117/12.3012471

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